“Online Customer Experience -
Does the type of device matter?”
Serpil Karaduman Student number: 2850214
University of Groningen – Marketing Department Master Thesis January 2016
First Supervisor: prof. dr. P.C. Verhoef Second Supervisor: dr. J. Hans Berger
Management Summary
In the last years online customer experience received much attention in scholarly journals. Its novelty and broad construct makes it interesting to discover its effects. Some authors argue that online customer experience is the main driver of success. Previous studies have investigated three categories in order to determine the key factors of online customer experience. You can find a collection of website quality, online customer behavior and online service experiences studies in the literature. However, Omni-channel experience becomes essential for retailers – it is important to create a seamless experience and achieve synergy effects by integrating online and offline experiences. Online customer experience can be categorized in a cognitive and emotional processing. The former describes how incoming stimuli is processed by individuals. The latter defines it as an affective response when individuals are exposed to particular features of a website. Since online sales have increased substantially where this upturn is attributed in particular to smartphones and tablets. According to technological developments in the recent past, this research studies four different types of devices in detail, namely smartphones, tablets and the conventional laptop or stationary PC. Therefore, this study has its purpose to explore the moderating relationship of the devices on the construct of online customer experience.
In order to test the defined hypotheses on the constructs perceived usefulness, perceived ease of use and entertainment, an online questionnaire was conducted (n = 158). First, this research starts with the analysis of the main relationships. The results of the main relationships show significant and positive relationships. This was also found in the literature. Accordingly, managers need to pay close attention on the constructs when developing an online presence or establishing an e-commerce website. This significant relationship can be explained by the opportunities generated for customers such as customization, convenience and especially accessibility of mobile devices. Second, as already mentioned earlier, this study has investigated the moderating effect of the devices. It was expected that mobile devices have a stronger effect on online customer experience. This was true for the first construct namely perceived usefulness. Conversely, perceived ease of use and entertainment was proved not to be significant. Only slight indication could be explored which denote that there might be some effects.
specifically regarding the e-commerce website to find weak points or you need to know the steps taken by the customer when visiting an online shopping platform.
Table of content
Management Summary ... I Preface ... II Table of content ... III
1 Introduction ... 5
1.1 Problem Statement Research Question ... 6
1.2 Relevance: Literature Contribution ... 7
2 Theoretical Framework ... 9
2.1 Online Customer Experience (OCE) ... 9
2.1.1 Customer Experience: Cognitive Processing ... 10
2.1.2 Customer Experience: Emotional Processing ... 11
2.2 Definition Types of Devices ... 12
2.3 Determinants of Website Quality ... 13
2.3.1 Perceived Usefulness (PU) ... 13
2.3.2 Perceived Ease of Use (PEOU) ... 15
2.3.3 Entertainment (EN) ... 17
2.4 Buying phase: search vs. purchase experience ... 19
3 Research Design ... 20
3.1 Analysis and Method Plan ... 22
4 Results ... 23
4.1 Sample description ... 23
4.2 Factor Analysis ... 25
4.2.1 Factor Analysis for the constructs of PU, PEOU and EN ... 25
4.2.2 Factor analysis for the constructs of the dependent variable ... 27
4.3 Regression Analysis – the effect of website quality on the construct of online customer experience ... 28
4.4 Moderation Analysis – the influence of the dimensions on customer satisfaction ... 29
4.5 Moderation analysis – the influence of the dimensions on customer delight ... 31
4.6 Search vs. purchase experience ... 35
5 Conclusion and Recommendations ... 36
5.1 Discussion ... 36
5.2 Managerial Implications ... 38
Appendix 1: Survey design ... I Appendix 2: Construct, scale items and references ... N
Table overview
Table 1: Sample Profile (n = 160) ... 23
Table 2: Output Factor Analysis ... 26
Table 3: Means and standard deviation of the constructs ... 27
Table 4: Mean and standard deviation on the constructs customer satisfaction and delight.... 28
Table 5: Multiple Regression of the constructs on customer satisfaction ... 28
Table 6: Multiple Regression of the constructs on customer delight ... 29
Table 7: Moderation analysis with device dummy of the dimension PU on customer satisfaction ... 30
Table 8: Moderation analysis with device dummy of the dimension PEOU on customer satisfaction ... 30
Table 9: Moderation analysis with device dummy of the dimension EN on customer satisfaction ... 31
Table 10: Moderation analysis with the device dummy of the dimension PU on customer delight ... 31
Table 11: Moderation analysis with the device dummy of the dimension PEOU on customer delight ... 32
Table 12: Moderation analysis with the device dummy of the dimension EN on customer delight ... 32
Table 13: Full model on the construct customer satisfaction ... 33
Table 14: Full model on the construct customer delight ... 34
Table 15: Overview of supported vs. not supported hypothesis ... 37
Figure overview Figure 2: Product categories ... 24
1 Introduction
The world has been experiencing a transformation process towards the Information Age since 1990. Advancements and developments in the Information Age have increased the importance of the Internet in a commercial way in terms of vital retail outlet for companies. Organizations have adjusted to the rapidly changing technological developments and adopted innovations in order to fulfill their customers’ changing needs. The landscape of traditional retailers has changed with the invention of the Internet. It is of upmost importance for retailers to guarantee superior customer experience in order to gain competitive advantage (Yarimoglu, 2014).
However, according to Yarimoglu (2014) online customer experience (OCE) can be defined as ‘a target customer perception and interpretation of the entire stimulus encountered while interacting a company and it includes the entire range of a visitor’s perceptions of a website’. The website of an online retailer can be categorized as a touchpoint for customers. These touchpoints create opportunities for organizations to communicate with customers, namely through recommendations, online word of mouth or interactivity, which can result in positive experiences and are able to give indications of the customer’s loyalty towards specific brands. Furthermore, organizations have explored these new potentials of e-retailing quickly and took action (Rose et al., 2010). Therefore, retailers have changed their business strategies in order to keep up-to-date with the changing technological environment and have become multi-channel retailers by setting up online shopping stores in addition to their brick-and-mortar stores (Melis et al., 2015).
Though e-retailers made heavy investments for corporate websites, some are still ineffective (Kim and Stoel, 2004). Nevertheless, prior studies have investigated the impact of features of website quality on customer satisfaction (Kim and Stoel, 2004; Bai et al., 2008). However, empirical research has not examined which website quality features influence customer delight in an online environment. Loiacano and colleagues (2002) have developed a measurement model of website quality, which comprises five elements such as usefulness, ease of use, entertainment, complimentary relationship and customer service. Furthermore, website visitors may have different purposes when visiting the online store. According to Baumgartner and Steenkamp (1996), consumer buying behavior can be distinguished into search and purchase phases that the consumer encompasses. In the present study this distinction will be taken into account.
(Verhoef et al., 2009). According to Carbone and Haeckel (1994) “customer experience takes place whenever a customer interacts with an organization and its activities.” A further definition of customer experience by Verhoef et al. (2009, p. 32) states, “customer experience is holistic in nature and involves the customer’s cognitive, affective, emotional, social and physical responses to the retailer.”
Nowadays, customers are able to access information and communicate with each other at any time as well as make online purchases. This was made possible by way of the previously mentioned technological advances (Rose et al., 2010). Though, it is beneficial to underline the importance of online shopping: The ever-increasing business-to-customers e-commerce revenue has generated a significant amount of money, $ 418.05 (in billion US dollars) in 2015 in European Countries and the forecast for 2018 continues to rise (Statista, 2015a). According to ecommercenews.eu (2015) prognosis, type of devices (PC, smartphone, tablet) will have an effect on mobile commerce. Whereas the traditional PC will probably be substituted within the near future and be outperformed by smartphone or tablet devices. There is an evident increase in tablet users and forecasts have shown that this will further increase for instance in Western Europe were 146.8 million users registered in 2014 (Statista, 2015b).
1.1 Problem Statement Research Question
According to Statista (2015), the number of tablet users in European countries will amount to 160 million by the end of 2015. As previously mentioned, the increase in e-commerce sales will continue. These figures illustrate the importance of e-commerce channels and emphasize the importance of website quality for organizations.
emotional and cognitive aspect of customer experience including the moderating effect of type of devices. Whereby this study contributes to the literature by comparing device types that are distinguishable in the element of being mobile or fixed.
To summarize, this research will focus on the following problem statement:
‘What is the impact of type of device (mobile vs. fixed) on the relationship between website quality factors and online customer experience (cognitive and emotional processing)?’
The problem statement is allocated separately into the following sub-research questions in order to provide an accurate answer following:
• How does perceived usefulness influence OCE and to what extent does the type of device moderate this?
• How does perceived ease of use influence OCE and to what extent does the type of device moderate this?
• How does entertainment influence OCE and to what extent does the type of device moderate this?
1.2 Relevance: Literature Contribution
A significant number of studies have been conducted in the field of online customer experience. Three main areas have been covered, namely ‘website quality’, ‘online customer behavior’ and ‘online service experience’ (Rose et al., 2010). However, due to lacking research in the literature regarding the type of device on which these were experienced, this study will address this aspect as a moderator and explore its impact on the relationship of customer experience in an online shopping environment.
underlines the importance of different types of devices for instance mobile channels or tablets (Verhoef et al., 2015) where customers seek an integration of digital and physical advantages (Rigby, 2011).
2 Theoretical Framework
One can derive from the conceptual model in figure 1 that this study examines the relationship of website quality determinants on cognitive and emotional response to online customer experience by means of customer satisfaction and customer delight. The conceptual model specifically takes into account two different types of devices namely mobile (smartphones and tablets) and fixed (laptop and stationary PC) devices. Moreover, this study additionally explores the online buying phases (search vs. purchase).
The following sections provide a brief definition about the types of devices, elaborating on the cognitive and emotional processing and a discussion about the website quality features. Furthermore, the different buying phases of customers are described.
2.1 Online Customer Experience (OCE)
The website of an e-retailer represents data in variety of ways, for instance stimuli can be presented as a text, images or information can be delivered by using videos or audio. Customers form their impressions while visiting the website of the e-retailer from a cognitive and an affective perspective (Rose et al., 2012). Additionally, customers might evaluate the given stimuli from an emotional viewpoint (Rose et al., 2010).
A substantial number of studies have investigated the drivers of online customer experience (OCE). Those can be classified mainly in three parts. First, there is a collection of literature
Website Quality: • Usefulness • Ease of Use • Entertainment Online Customer Experience: Cognitive Emotional Type of device: mobile vs. fixed device
customer behavior regarding search and purchase activities (Kumar et al., 2005; Grant et al., 2007). Third, a significant domain of research has paid attention to online service experiences (Khalifa and Liu, 2003; Lee and Lin, 2005). According to Rose et al. (2012) website quality determinants display the first milestone for uncovering OCE. Online shopping differs in some facets with traditional brick-and-mortar stores, for instance a traditional retailer offers in-store atmospheric features like music, color and assortment, whereas e-commerce has its mere touchpoint explicitly on the website, which can be accessed through different devices. The interaction with customers is based on an automated interface with one-way communication possibilities. However, it enables companies to decrease their costs (Chen & Dubinsky, 2003). In order to curtail the broad construct of online customer experience, this research measures customer experience through customer satisfaction and customer delight, which has already been used by different authors in previous research papers (Lin, 2007; Eid, 2011). By doing so, the author supposes to cover both dimensions of cognitive and emotional customer experience in this research. In their article Frow and Payne (2007) draw the conclusion that cognitive and emotional processing can be described as a part of the customer experience, which will be discussed subsequently. The web experience is a crucial element for multi-channel retailers and especially for e-retailers that lack an offline environment. Thus, a dysfunctional website would impact customers in an undesirable way. In line with this, multi-channel retailers may create a synergy effect by integrating online and physical store experience (Constantinides, 2004). Nowadays, companies are pressured to create a seamless Omni-channel experience through all customer touchpoints, for instance desktop, laptop, mobile device or a branded app. It is important to take all these available channels into account, because the total customer experience is formed through constantly switching between them (Verhoef et al., 2015).
2.1.1 Customer Experience: Cognitive Processing
The cognitive approach can be categorized as a memory-based evaluation. As a consequence of cognitive processing customer satisfaction can be stated as an accumulation of customer experience (Rose et al., 2011). Novak et al. (2000) developed a model to measure OCE in terms of website flow, it is seen as a cognitive experience. The authors have determined several variables such as skill and control, challenge and arousal, focused attention, interactivity and telepresence in order to assess OCE. The authors further argue that consumers who experience a flow while being on a particular website experience thoughts and perceptions which lead to definite gratification. In other words “flow” itself is a cognitive construct, which is associated with “enjoyment, involvement, concentration and intrinsic interest”, so Huang (2006). Customer satisfaction generates positive outcomes that are fruitful for any online retailer. Results of the study by Zeithaml (2000) state that customer retention, positive word-of-mouth and an increase in profits can be achieved when customers are satisfied. Lin (2007) explored the effect of website quality features on customer satisfaction. The results underline the importance of diverse website quality factors (“system quality, information quality and service quality”), where system quality (website design, interactivity) has a significant effect on customer satisfaction. The author argues that website comprises following characteristics - design, reliability and ease of use. Moreover, security of transactions places an enormous impact on customer satisfaction. Kim and Stoel (2004) conducted a research in which website quality determinants developed by Loiacano affected customer satisfaction within an apparel retailer. They found that information-fit-to-task transaction capability and response time (belongs to PU) have the strongest effect on customer satisfaction.
2.1.2 Customer Experience: Emotional Processing
surprise and joy. As in a consumption situation, delight is created by means of joy and surprise; the author’s categorize delight as an arousal and positive emotion (Verma, 2003). Some authors examined the antecedents of customer delight and discussed that a noteworthy performance or satisfaction triggers arousal, which turns into a positive affect (pleasure), thereafter affecting customer delight. Furthermore, the authors argue that delight results in revisit intentions (Oliver et al., 1997).
2.2 Definition Types of Devices
individualized – it carries the user’s identity compared to fixed devices (Lee and Benbasat, 2004).
This study treats mobile devices (smartphone and tablets) together and distinguishes it from fixed devices such as PC`s and laptops in order to have sufficient respondents who fit the requirements. Furthermore, smartphones and tablets are close to each other in their appearance also these devices are location-independent. On the other hand, PC`s and laptops are generally associated with task-oriented issues or at home usages.
2.3 Determinants of Website Quality
The website as an interaction point for experiences can be described on different quality dimensions (Mahlke, 2002). Loiacano and colleagues (2002) developed a measurement model for website quality (e-commerce selling books, tickets, CDs etc.) by reviewing marketing and information system literature. This present study has its focus on the following determinants of website quality by Loiacano et al. (2002) usefulness, ease of use and entertainment, which will be discussed extensively in the subsequent section. Since the website of organizations or e-retailers serve as a communication tool (Loiacano et al., 2002). This research has determined its focus on website quality determinants, because it is a starting point for online customer experience (Rose et al., 2012). Two other dimensions (Complimentary relationship, customer service) are left out due to perceived overlap to the beforehand mentioned dimensions and are also set as a limitation. And some items were included from a second paper by Malhotra et al. (2000).
2.3.1 Perceived Usefulness (PU)
Davis (1989) has developed the Technology Acceptance Model (TAM), which discovers difficulties that may appear before users are exposed to a particular system. Also, TAM determines that customers acceptance of technological systems depends on two factors namely perceived usefulness (PU) and perceived ease of use (PEOU) (The latter will be described subsequently).
customers are already in the store (Hui et al., 2013), which may increase PU for mobile devices, because customers may feel that they have closed a clever deal during their shopping trip. Mobile devices are generally used for information gathering that offers more flexibility and easiness. Moreover, the greater size of the screen of tablet devices provides a more convenient view of products and a better visibility of payment forms. It is likely that once customers have adopted the tablet into their daily routines, it would fit into their task objectives, because one can assume that tablets are in-between smartphones and fixed devices, so the iPad developer Steve Jobs. Also, previous studies have shown that mobile phones are used for information gathering on the go, thus the author expects that this effect would be suitable for tablets as well, since these devices are characterized with greater screen sizes and the touch interaction fosters easy navigation. In terms of trust, the author assumes that consumers who once adopted the tablet would not experience trust deficiencies. However, stationary devices do not fulfill characteristics such as flexibility or full-time accessibility. It is reasonable to assume that the effect of PU would be stronger for mobile devices compared to fixed devices. Following this argumentation, it is likely to hypothesize that the type of device interacts with usefulness to moderate the relationship between PU and OCE. Due to the novelty of tablets, consumers may be more critical on the usage, online shopping trust issue and websites that are not suited for tablets which creates a greater impact on customer experience. Therefore, the moderating effect of mobile devices will be explored, but the main effect will be hypothesized as followed:
H1: Perceived usefulness of a website has a positive effect on online customer experience.
2.3.2 Perceived Ease of Use (PEOU)
interaction with the content of the device. These changes in entering types offer less effort and skills needed. Therefore, customers can accomplish tasks with “greater ease, comfort and confidence” (Ally and Gardiner, 2012). Mobile devices offer a touch-based service, several authors found that touch-based access to diverse contents are easy to learn and use; this simplicity of the technology is valued by the users (Isomursu et al., 2008; Riekki et al., 2006; Välkkynen et al., 2006a). Moreover, the touch-based interaction with the content leads to an enhanced experience and provides a solution for remembering long URLs. Besides, seamless experience can be created by the integration of physical and digital worlds (Isomursu and Ervasti, 2009).
The author expects that the effect of PEOU on OCE would be stronger for mobile devices for several reasons: mobile devices are closely linked to intuitive navigation through touch interaction, high-resolution display, greater ease of use by touch and voice interaction and less cognitive effort needed due to presented information as images (icons). Todays busy environment forces people to save time and close transactions easily, for instance doing groceries online, which would improve daily efficiency. Furthermore, mobile devices offer accessibility and convenience due to their portability, whereas fixed devices are for in-home tasks or work related utilization. It takes less effort to use a mobile device compared to a fixed device, because switching to a fixed device takes more time even when customers are at home on their sofa (Manning, 2015). Therefore, the following hypotheses would be examined:
H2: The positive effect of perceived ease of use on online customer experience will be stronger
for mobile devices than for fixed devices.
2.3.3 Entertainment (EN)
more fun compared to desktops, whereas wireless phones were less fun than desktops (Bruner and Kumar, 2005). Furthermore, adding playful features differentiate websites from each other, which positively affects customer satisfaction (Cao et al., 2005). Constantinides (2002) refers to the aesthetics in terms of a websites atmosphere whether it is able to persuade and invite visitors to explore and even interact with the particular website, which is distinct to a physical store. The author further argues that online customers spend less time on online browsing compared to a physical browsing, where it is a challenge for online retailers to attract interest and welcome new visitors. A study at Stanford University shows that website design is one of the most important factors affecting the credibility of online retailers (Fogg et al., 2002).
Mobile devices are increasingly used for entertainment matters such as online shopping, gaming etcetera. Conversely, fixed devices are generally used for task-related issues. It can be argued that mobile devices are fun related devices and fixed devices are more work related. Therefore, the entertainment factor of mobile devices should be stronger compared to fixed devices.
It is likely to assume that mobile device users are consuming their mobile devices for entertainment matters more often compared to fixed devices. Especially consumers who appreciate visuals (icon, images) would have a greater entertaining factor with mobile devices, enjoy and perceive it as more positive visiting particular e-retailers website, due to the fact that the design of websites are in general more visualized (for instance icons) information, considering limited screen size – less space for extended content. In other words, consumers who seek entertainment while they are commuting or waiting at the train station would have a more positive experience when using their mobile devices compared to stationary devices. Hence, the author hypothesizes the following hypotheses:
H3: The positive effect of entertainment on online customer experience will be stronger for
2.4 Buying phase: search vs. purchase experience
The total customer experience comprises of search, purchase, consumption and after-sales phases, which is highly important in today’s multi-channel setting, because customers can visit different channels and those may affect each other (Verheof et al., 2009). This study takes into account two predetermined experiences namely search and purchase.
3 Research Design
The research design of this particular study follows the structure of Malhotra (2010) namely “a) kind of information obtained b) method of administering the questionnaire c) scaling techniques d) nature of the questionnaire e) sampling plan and size”.
a) Kind of information obtained:
In order to conduct this research, the author reviewed relevant literature in academic journals (e.g. Journal of Retailing, Journal of Business Research, Harvard Business Review) on several databases (Google Scholar, ProQuest) to achieve necessary knowledge and to find underlying dimensions of the constructs of online customer experience and website quality determinants. The theoretical framework was developed according to academic journals. Moreover, a web-based survey was established for the measurement of the independent and dependent variables, which can be found in the appendix 1.
b) Method of administering the questionnaire:
The questionnaire will be spread on social media channels such as Facebook, Twitter, LinkedIn and Xing and via E-Mails due to the rapid digital dissemination. The author believes that with this distribution method a large number of respondents can be generated and a high variability among respondents can be achieved. Few requirements need to be fixed before starting with the questionnaire. These include that the respondents have to be familiar with one of the devices stated and have at least once visited a particular online shopping website.
c) Scaling techniques:
d) Nature of the questionnaire:
First, the questionnaire involves demographic questions such as age, gender, nationality and living area. Secondly, a filter question was included in order to conduct the moderation effect by means of choosing one of the device types offered for online shopping purposes. Third, by asking the respondents which website they remember most, they are asked to answer the questions by recalling a particular website from their mind and completing the survey with questions related to website quality determinants. Finally, two questions were derived from existing scales to measure cognitive and emotional customer experience (Finn, 2005). The former was assessed in terms of customer satisfaction and the latter by means of customer delight. An additional question was included in order to consider, which devices were used by respondents in a particular decision-making process (search, purchase) by using a scale from one to five. The questionnaire was developed by Loiacano and colleagues (2002) to examine website quality determinants, which will be used in this research. Loiacano’s WebQualTM was used in several studies (Kim et al., 2004; Sinnappan et al., 2005; Everard et al., 2009;). The survey consists of 9 general questions and 32 questions about website quality items which will be spread among English speaking people.
The questionnaire was set up with online questionnaire development tool Qualtrics. This survey method was used, because of its simplicity and reliability, hence respondents reply to a fixed question set and have to select from predetermined statements. Furthermore, the variability of individual responses can be reduced by means of fixed questions (Malhotra, 2010).
e) Sampling plan and size:
3.1 Analysis and Method Plan
4 Results
4.1 Sample description
A total of 183 respondents were collected mainly by means of social media channels. Based on the dropout rate of 8% and incomplete surveys, the process of data cleaning resulted in 158 remaining respondents that will be used for further analysis.
The data consists of 74 male and 84 female respondents. Additionally, the age category that is represented the most is 25 to 34 years, followed by 19 to 34 years. A screening question was placed in the beginning of the survey which made it possible to pre-select respondents if they meet the requirements of using an online shopping website at least once, only one respondents had never an experience with online shopping. The remaining respondents are in the following categories: 43,1% “less than once a month”, 35,6% “once a month”, 18,1% “2-3 times a month and 1,3% in the categories “once a week” and “2-3 times a week”. According to the analysis, it can be assumed that the respondents are highly familiar with online shopping as well as skillful using several e-commerce websites.
Table 1: Sample Profile (n = 160)
Demographics N Percentage (%) Gender Male Female 74 86 46,3 53,8
Age Under 18 years
19 to 24 years 25 to 34 years 35 to 44 years 45 to 54 years 3 44 105 7 1 1,9 27,5 65,6 4,4 0,6
How often do you shop online?
Never
However, the sample depicts respondents that differ in which device they use the most when online shopping - 15% have indicated that they have used their smartphone, while 15,6% have used their tablet. A substantial percentage (59,4%) has used their laptop and only a minor percentage (9,4%) has used their stationary PC for online shopping purposes.
Due to similarities between the devices smartphone and tablet, the author has decided to combine these two groups into the mobile device condition and to accumulate the group of laptop and stationary PC users into fixed device users. Also, with regards to meet the sufficient respondents level in the mobile device condition, thus in order to be able to proceed with the analysis. Therefore, the mobile condition comprises 49 respondents and the second condition (fixed) has 110 respondents.
Several product categories are placed in the survey and the results display that respondents mostly buybooks (66%), Electronics (70%), Apparel (51%), Groceries (5,6%), Big household appliances (12,5%), Small household appliances (31,2%), personal care (35%).
Figure 2: Product categories
Among the respondents a great variability of nationalities across Europe can be found. Therefore, the results of this analysis should hold across diverse nationalities. The nationalities are Austrian (25%), German (25%), Turkish (26%) and Dutch (8%). The remaining nationalities are among Bulgarian, Spanish, Finnish, Romanian, Greek, Italian, Hungarian and Czech citizen.
4.2 Factor Analysis
Two separate factor analysis were conducted to combine several items into factors due to multicollinearity issues. First, the items belonging to the independent variables and secondly the items comprising the dependent variables are combined.
4.2.1 Factor Analysis for the constructs of PU, PEOU and EN
In order to reduce dimensions within the analysis, a factor analysis was run with all the items included. Due to low communalities (below 0.4) several items were dropped from the analysis in the first place.
Model fit was assessed by Kaiser-Meyer-Olkin Measure of Sampling Adequacy, which is greater than 0.5 (0.911). Bartlett’s Test of Sphericity was significant (p = 0.000). The remaining 23 items crossed the cut-point value of 0.4 regarding communalities. The results presented a three-factor solution with an Eigenvalue of 1,763 explaining 65.748% of the total variance. The Varimax rotation was used to identify high loadings on factors. It is true that the items share some common variance.
Table 2: Output Factor Analysis
Construct name Items Component
1 2 3
Communality Alpha
PEOU My interaction with the website is clear and understandable. The website labels are easy to understand.
I find the website easy to use.
The display pages within the website are easy to read. The text on the website is easy to read.
Learning to operate the website is easy for me. The website adequately meets my information needs. The website is flexible to interact with.
The website is well organized.
The website is useful for searching for and buying goods.
The information on the website is pretty much what I need to carry out my tasks. This website makes it easy to find what I need.
The Information on the website is effective.
.832 .828 .786 .777 .775 .757 .633 .610 .600 .421 .588 .522 .580 .536 .495 .505 .850 .833 .787 .763 .759 .749 .796 .775 .770 .442 .714 .759 .708 .681 .686 .648 .600 .523 .538 .646 .662 .446 .685 EN PU
I have fun using the website. I find using the website enjoyable. The website is visually pleasing.
Using the website to purchase provides me with a lot of enjoyment. The website displays pleasing design.
The actual process of using the website is pleasant.
The website increases my productivity when searching for and purchasing goods. The website enhances my effectiveness in goods searching and purchasing. The website improves my performance when searching for purchasing goods The website makes it easier to search for and purchase goods.
Descriptive statistics was computed with the combined items, which shows that PEOU is the most important construct, followed by PU and EN, that can be classified as the least important when comparing the mean values.
Table 3: Means and standard deviation of the constructs
Construct N M SD PU 158 5.2706 1.05538 PEOU EN 158 5.8413 .75692 158 5.0612 1.14212
4.2.2 Factor analysis for the constructs of the dependent variable
The second factor analysis was performed to combine the dependent variables in the model. The model fit was assessed by Kaiser-Meyer-Olkin (KMO) of Sampling Adequacy, which resulted in a value of 0.778 that is above the cut-off value 0.5. Additionally, Bartlett’s Test of Sphericity was verified to be significant (p = 0.000). Subsequently, a communalities check demonstrated that all included items were above the cut-point value 0.4. According to the Eigenvalue the items should be combined into two factors (1.536). These items together explain 69.022 % of the total variance. Once again Varimax rotation was used to illustrate marker items.
Finally, to proof reliability of the scale and internal consistency Cronbach’s Alpha was conducted. At a level of 0.807, which is relatively high, hence we can conclude that the scale is reliable. As a final step, one needs to look in the table “if item deleted” there we can see if the overall alpha increases when deleting one of the items. In this case, one item namely “Gleeful” would have increased the overall alpha but only a minor value (0.008). Therefore, the author decided to keep this specific item. Customer Satisfaction was measured on a scale of “7=strongly disagree” to “1=strongly agree”. Customer Delight was measured on a scale of “5=Never” to “1=always”.
Table 4: Mean and standard deviation on the constructs customer satisfaction and delight
Construct n M SD
CS 158 5.5506 .91770
CD 158 3.0063 .76870
4.3 Regression Analysis – the effect of website quality on the construct of online customer experience
In order to assess whether the constructs of website quality have an impact on the online experience a regression analysis was conducted with the defined constructs in the previous step by running a factor analysis. A multiple regression was conducted to predict customer satisfaction from perceived usefulness (PU), perceived ease of use (PEOU) and entertainment (EN). The result of this regression analysis was significant, R2 = 0.631, F(3,154) = , p < 0,05. Hence, the independent variables explain 63,1% of the variability of the dependent variable. Moreover, the model is a good fit of the data. The coefficient results demonstrate that all independent variables have a significant impact on customer satisfaction. The construct perceived usefulness significantly predicts customer satisfaction (β = 0,139, p < 0,05), also perceived ease of use (β = 0,640, p < 0,05) and entertainment (β = 0,188, p < 0,05). In other words, for increases in the constructs perceived usefulness, perceived ease of use and entertainment customer satisfaction will be affected positively. In particular, the construct perceived ease of use has by far the greatest impact on customer satisfaction. According to the results, support was found for Hypothesis 1 – “Perceived usefulness of a website has a positive effect on online customer experience”.
Table 5: Multiple Regression of the constructs on customer satisfaction
Construct B p-value VIF
To further assess the influence of the dimensions on the construct customer delight a subsequent step was performed. The author has additionally run a multiple regression to explore whether perceived usefulness, perceived ease of use and entertainment has an influence on customer delight. The result of this multiple regression was significant R2 = 0.360, F(3,154) = , p < 0,05. The constructs in the model explain only 36% of the variability of the dependent variable (customer delight). The model is a good fit of the data. The coefficient results of this analysis exhibit that perceived usefulness significantly predicts customer delight (β = 0,220, p < 0,05) as perceived ease of use (β = -0,157, p < 0,05). Entertainment is marginally significant (β = 0,322, p < 0,1), when the significance level is increased to p < 0,1. However, for increases in the construct perceived usefulness and entertainment customer delight will be affected positively. Interestingly, an increase in the construct perceived ease of use customer delight will be affected negatively. In this model, entertainment has the greatest influence on customer delight.
Table 6: Multiple Regression of the constructs on customer delight
Construct B p VIF PU .220 .000 1.638 PEOU EN -.157 .069 1.717 .322 .000 1.584 R2 = .360, R2 adjusted = .347
To sum it up, it can be concluded that the defined constructs by reviewing existing literature certainly affect online customer experience on both dimensions.
4.4 Moderation Analysis – the influence of the dimensions on customer satisfaction
A moderation analysis was conducted to explore whether the type of device moderates the relationship between the constructs and customer satisfaction as well as customer delight. The variable type of device was performed with dummy variables, where smartphones and tablets were combined into one variable; this category received the coding 1. As the benchmark category laptop and PC devices received the coding 0. These dummy variables were used to create the interaction effect between the independent variables.
conducted. Second, the construct of perceived ease of use was assessed and subsequently as a third step, the moderating effect of type of device on the relationship between entertainment and customer satisfaction was investigated.
First, the interaction effect between type of device and PU on customer satisfaction is significant p-value (p < 0.010). It can be concluded that the construct perceived usefulness is stronger for mobile devices compared to fixed devices. However, the main effect is still supported (p < 0.000). Device as a moderator has also a significant effect on the construct of customer satisfaction.
Table 7: Moderation analysis with device dummy of the dimension PU on customer satisfaction Construct B p-value Constant 3.367 .000 PU Device dummy PU*device dummy .411 - 1.725 .000 .012 .322 .010 R2 = .370, R2 adjusted = .357
Second, the author investigated the interaction effect of type of device and perceived ease of use on customer satisfaction. The interaction effect of perceived ease of use and the type of device dummy on customer satisfaction is not significant. At a level of p < 0.230 that means that the effect of perceived ease of use on customer satisfaction is not stronger when the device is mobile compared to the fixed device. Therefore, the second hypothesis “The positive effect of PEOU on OCE will be stronger for mobile devices than for fixed devices” is not supported.
Third, the interaction effect of entertainment and device dummy was assessed. This result provides no evidence for the third hypothesis “The positive effect of EN on OCE will be stronger for mobile devices than for fixed devices”, due to a non-significant p-value (p < 0.923). Surprisingly, the dimension entertainment is not stronger on customer satisfaction when the device is mobile.
Table 9: Moderation analysis with device dummy of the dimension EN on customer satisfaction Construct B p-value Constant 3.252 .000 EN Device dummy EN*device dummy .454 .000 -.915 .169 .182 .184 R2 = .371, R2 adjusted = .366
4.5 Moderation analysis – the influence of the dimensions on customer delight
In order to explore the second dependent variable customer delight in the model, the author conducted a subsequent moderation analysis for the construct to investigate the moderating effect of the type of devices on the relationship between the constructs and dependent variable. The moderator device was coded as a dummy variable. As benchmark the category fixed “laptop and PC devices” received a 0 and all else (smartphone and tablet devices) received the coding 1. Table 10 illustrates the results of the interaction effect, which is not significant. That means that, the construct perceived usefulness is not stronger for mobile devices compared to fixed devices. However, once again there is evidence for the main effect, which was hypothesized in Hypothesis 1 (p < 0.000).
Second, the author investigated the interaction effect of type of device and perceived ease of use on customer delight. The interaction effect of perceived ease of use and the type of device dummy on customer delight is not significant. At a level of p < 0.625 that means that the effect of perceived ease of use on customer delight is not stronger when the device is mobile compared to the fixed device. Therefore, the author found no evidence for the second hypothesis “The positive effect of PEOU on OCE will be stronger for mobile devices than for fixed devices”.
Table 11: Moderation analysis with the device dummy of the dimension PEOU on customer delight Construct B p-value Constant 1.465 .013 PEOU Device dummy PEOU*device dummy .249 .003 -.174 .077 .853 .625 R2 = .110, R2 adjusted = .093
Finally, the third construct entertainment was assessed with the device dummy variable to explore the relationship. The interaction is not significant. Therefore, there is no support for the Hypothesis 3 of the construct of entertainment on the output ofcustomer delight. Thus, the dimension entertainment is not stronger when the device is mobile compared to fixed devices.
To conclude, the dimensions perceived usefulness, perceived ease of use and entertainment have a significant positive influence on customer satisfaction and customer delight within an online shopping environment. The main finding in this study exhibits that there is some indication that the type of device may play a role, but the author thinks that a substantial data is needed to explore this particular assumption to find significant values.
As a final step, the full model was assessed on the constructs of customer satisfaction (Table 13) and on the construct of customer delight (Table 14). The full model on the construct of customer satisfaction shows significant positive relationship on the dimension perceived ease of use (PEOU) and entertainment (EN). This means that if PEOU and EN goes up, customer satisfaction will go up as well. In the full model, the interaction effects were not significant.
Table 13: Full model on the construct customer satisfaction
The concluding analysis in this research was conducting the full model on the construct of customer delight. The following table (Table 14) shows the results of a moderation analysis. All main effects namely perceived usefulness (PU), perceived ease of use (PEOU) and entertainment (EN) have a significant effect on customer delight. Once again, the interaction effects show no significance.
Table 14: Full model on the construct customer delight
4.6 Search vs. purchase experience
Due to the difficulty of hypothesizing the search and purchase experience of customers, this relationship was explored. According to figure 3, it can be stated that respondents indeed use their smartphones and tablets for aquick information search. It can be argued that customers use their mobile devices, when they are on the go, due to the handiness, the ease of use of mobile devices and the fact of fast task completion customers. Customers still use their fixed devices for the actual purchase, this can traced back to the fact of trust or privacy concerns customers may have. Therefore, the author found evidence for the fact that mobile devices are in general used for quick information searches, while fixed devices are used for the actual purchase.
Figure 3: Interaction of mobile and fixed devices 0 10 20 30 40 50 60 70 80 90 100
quick information search actual purchase
5 Conclusion and Recommendations 5.1 Discussion
Table 15 provides an overview of supported and not supported hypotheses in this research. The first hypothesis that perceived usefulness has a positive influence on online customer experience is supported. This means that PU has a significant positive relationship with the constructs customer satisfaction and customer delight. The second hypothesis, which implies that perceived ease of use will be stronger for mobile devices compared to fixed devices, is not confirmed in this study. Finally, no evidence was found for the third hypothesis that the relationship between entertainment and customer experience will be stronger for mobile devices than for fixed devices. According to the closeness between p-values to the significance levels, it can be concluded that a slight interaction effect may exist.
Lastly, this research finds support for the fact that respondents use their mobile devices for quick information search. This can be attributed to the easiness of these devices and accessibility to the Internet and particular e-commerce websites while they are commuting. Respondents have indicated that actual purchases are made on their more fixed devices, which can be attributed to the fact that for instance a laptop is perceived as more trustworthy. Due to the novelty of tablet devices, customers are more concerned with privacy and trust issues.
Table 15: Overview of supported vs. not supported hypothesis
Hypothesis Supported/not supported H1a: Perceived usefulness of a website has a positive effect
on customer satisfaction.
H1b: Perceived usefulness of a website has a positive effect on customer delight.
H2a: The positive effect of perceived ease of use on customer satisfaction will be stronger for mobile devices than for fixed devices.
H2b: The positive effect of perceived ease of use on customer delight will be stronger for mobile devices than for fixed devices.
H3a: The positive effect of entertainment on customer satisfaction will be stronger for mobile devices than for fixed devices.
H3b: The positive effect of entertainment on customer delight will be stronger for mobile devices than for fixed devices. Supported Supported Not supported Not supported Not supported Not supported
5.2 Managerial Implications
Managers of e-commerce channels may pay attention on the website design and the usability of their website. This means that technology in the area of devices is changing constantly. Therefore, it is important to pay careful attention to the development of a mobile-friendly website - “responsiveness” is the key. This means that a particular website can be accessed through different websites and the website adjusts itself to specific devices. Also, managers need to pay in the same way attention to the desktop version of their websites due to no major differences between devices. In order to guarantee a seamless experience, managers may undertake for instance usability tests with potential visitors. By doing so, managers are enabled to discover “moments of truth” within the customer journey. Unsatisfying touchpoints during online shopping can be discovered and subsequently improved to assure customer satisfaction and delight, which in turn may have an impact on both purchase and revisit intention. By adapting these changes along the customer journey a positive online customer experience will be achieved, especially affecting the dimensions customer satisfaction and delight.
5.3 Limitations and future research
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Appendix 1: Survey design
Dear participant,
As a final assignment for my MSc Marketing Management, I have to design and conduct a research in a relevant marketing field. My field of research is Customer Experience, focusing on Online Customer Experience - this is how customers evaluate a website in terms of its quality and how different factors can moderate this evaluation. Following you will be presented a set of questions to assess this effect; it will take between 5 to 10 minutes.
Thank you for your time and participation, Serpil Karaduman.
Part 1: Demographic questions: What is your gender?
O female O male
In which category is your age? O under 18 years O 19 to 24 years O 25 to 34 years O 35 to 44 years O 45 to 54 years O 55 to 64 years O Age 65 or older What is your nationality?
Fill in:
In which city are you currently residing? Fill in:
What is the highest educational level you have obtained? O less than secondary/high school
O secondary/high school
O some college or university, no degree O Bachelor’s degree
O Master’s degree
O Graduate or professional degree
O 5 to 8 times a month O 9 to 12 times a month O 13 or more times a month Part 2: Filter Question:
How often do you shop online? O Once a week
O Once a month,
O Never ( end survey)
When shopping online which device do you use the most? O Mobile
O Tablet O Laptop
O Stationary PC
Matrix with different devices:
Indicate for what do you use each device with 1=to quick information search and 5= actual purchase (leave out those devices you do not use):
Quick information search Actual purchase Smartphone
Tablet Laptop PC
What kind of products do you buy online? (multiple options possible) O Groceries
O Apparel O Electronics
O Big household appliances O Small household appliances O Personal care
For the following sections, we request you to think of a website you have shopped at, from which search or purchase you can recall the details of the website.
Fill in website: _________ (e.g. amazon etc.)
What did you buy? _________ (e.g. book, jeans etc.)
Please, from now on answer the questions we will expose you to about the website you just filled in.
Which device have you used for your online shopping? O mobile device (smartphone, tablet)
O fixed device (PC, laptop)
Part 3: Website quality
“1 = completely disagree” and “7 = completely agree”
Item Perceived Usefulness (PU):
The information on the mobile/desktop website is pretty much what I need to carry out my tasks.
1 2 3 4 5 6 7
The mobile/desktop website adequately meets my information needs.
1 2 3 4 5 6 7
The information on the mobile/desktop website is effective.
1 2 3 4 5 6 7
The mobile/desktop website allows me to interact with it to receive tailored information.
1 2 3 4 5 6 7
The mobile/desktop website has interactive features, which help me accomplish my task.
1 2 3 4 5 6 7
I can interact with the mobile/desktop web site in order to get information tailored to my specific needs.
1 2 3 4 5 6 7
When I use the mobile/desktop web site there is very little waiting time between my actions and the web site’s response.
1 2 3 4 5 6 7
The mobile/desktop website loads quickly.
1 2 3 4 5 6 7
The mobile/desktop website takes long to load.
1 2 3 4 5 6 7
This mobile/desktop website makes it easy to find what I need.
1 2 3 4 5 6 7
It makes it easy to get anywhere on the site.
1 2 3 4 5 6 7
It enables me to complete a transaction quickly.
1 2 3 4 5 6 7
